Scalable Uncertainty Management : 11th International Conference, SUM 2017, Granada, Spain, October 4-6, 2017, Proceedings /
This book constitutes the refereed proceedings of the 11th International Conference on Scalable Uncertainty Management, SUM 2017, which was held in Granada, Spain, in October 2017. The 24 full and 6 short papers presented in this volume were carefully reviewed and selected from 35 submissions. The b...
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Corporate Authors: | |
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Group Author: | ; ; ; |
Published: |
Springer International Publishing : Imprint: Springer,
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Publisher Address: | Cham : |
Publication Dates: | 2017. |
Literature type: | eBook |
Language: | English |
Series: |
Lecture Notes in Computer Science,
10564 |
Subjects: | |
Online Access: |
http://dx.doi.org/10.1007/978-3-319-67582-4 |
Summary: |
This book constitutes the refereed proceedings of the 11th International Conference on Scalable Uncertainty Management, SUM 2017, which was held in Granada, Spain, in October 2017. The 24 full and 6 short papers presented in this volume were carefully reviewed and selected from 35 submissions. The book also contains 3 invited papers. Managing uncertainty and inconsistency has been extensively explored in Artificial Intelligence over a number of years. Now, with the advent of massive amounts of data and knowledge from distributed, heterogeneous, and potentially conflicting sources, there is i |
Carrier Form: | 1 online resource (XIX, 438 pages): illustrations. |
ISBN: | 9783319675824 |
Index Number: | Q334 |
CLC: | TP18-532 |
Contents: | Invited papers -- Maximum likelihood estimation and coarse data -- Reasons and Means to Model Preferences as Incomplete -- Fuzzy Description Logics - A Survey -- Regular papers -- Using k-specificity for the management of count restrictions in flexible querying -- Comparing Machine Learning and Information Retrieval-based Approaches for Filtering Documents in a Parliamentary Setting -- Eliciting Implicit Evocations using Word Embeddings and Knowledge Representation -- K-nearest neighbour classification for interval-valued data -- Estimating Conditional Probabilities by Mixtures of Low Order |